Title: Moth flame optimisation based timetabling tool for educational course timetabling

Authors: Marisa Kuntasup; Pupong Pongcharoen; Thatchai Thepphakorn

Addresses: Department of Industrial Engineering, Faculty of Engineering, Naresuan University, 99 Moo 9, Thapo Sub-district, Muang District, Phitsanulok, 65000, Thailand; Faculty of Business Administration and Accountancy, Phitsanulok University, 93 Moo 5, Samo Khae Sub-district, Muang District, Phitsanulok, 65000, Thailand ' Department of Industrial Engineering, Faculty of Engineering, Naresuan University, 99 Moo 9, Thapo Sub-district, Muang District, Phitsanulok, 65000, Thailand ' Faculty of Industrial Technology, Pibulsongkram Rajabhat University, 156 Moo 5, Plaichumpol Sub-district, Muang District, Phitsanulok, 65000, Thailand

Abstract: Educational timetabling plays an important role in providing academic activities under limited time and resources. It determines the effective utilisation of teachers' and students' hours with no conflicts on resource constraints and individual preferences. Manually solving large-scale timetabling problems is time consuming and extremely difficult to find a good feasible solution. This paper presents the first application of discrete moth flame optimisation (MFO) for solving university course scheduling problems. A novel automated MFO-based timetabling (AMFOT) tool was programmed and tested using six case studies obtained from a collaborating university in Thailand. The computational experiments confirmed that all timetables generated by the proposed AMFOT tool were feasible as they satisfied all hard constraints. The timetables obtained from the proposed MFO method were better than those obtained from another computational intelligence based algorithm. In four out of six cases (66.67%), the best timetables were created by using the proposed MFO method.

Keywords: crow search algorithm; CSA; course scheduling; automated timetabling; swarm intelligence; resource allocation; moth flame optimisation; MFO.

DOI: 10.1504/IJIL.2025.148422

International Journal of Innovation and Learning, 2025 Vol.38 No.3, pp.282 - 300

Received: 31 Mar 2024
Accepted: 15 Jul 2024
Published online: 04 Sep 2025 *

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